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Research of facial feature extraction based on MMC
Author(s): Donglin Xue; Jiufen Zhao; Qinhong Tang; Shaokun Shi
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Paper Abstract

Based on the maximum margin criterion (MMC), a new algorithm of statistically uncorrelated optimal discriminant vectors and a new algorithm of orthogonal optimal discriminant vectors for feature extraction were proposed. The purpose of the maximum margin criterion is to maximize the inter-class scatter while simultaneously minimizing the intra-class scatter after the projection. Compared with original MMC method and principal component analysis (PCA) method, the proposed methods are better in terms of reducing or eliminating the statistically correlation between features and improving recognition rate. The experiment results on Olivetti Research Laboratory (ORL) face database shows that the new feature extraction method of statistically uncorrelated maximum margin criterion (SUMMC) are better in terms of recognition rate and stability. Besides, the relations between maximum margin criterion and Fisher criterion for feature extraction were revealed.

Paper Details

Date Published: 21 July 2017
PDF: 7 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 1042005 (21 July 2017); doi: 10.1117/12.2285410
Show Author Affiliations
Donglin Xue, Xi'an Research Institute of Hi-Tech (China)
Jiufen Zhao, Xi'an Research Institute of Hi-Tech (China)
Qinhong Tang, Xi'an Research Institute of Hi-Tech (China)
Shaokun Shi, Xi'an Research Institute of Hi-Tech (China)


Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

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